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  • Home
  • Publications
  • Springer Book
    • Table of Content
    • Chapter 1
    • Chapter 2
    • Chapter 3
    • Chapter 4
    • Chapter 5
    • Chapter 6
    • Chapter 7
    • Chapter 8
    • Chapter 9
    • Chapter 10
    • Chapter 11
    • Chapter 12
    • Errata
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  • DATA SETS
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Chapter 9: Semi- and Nonparametric Forecasting

Data Sets
Chapter-9-data.zip
Duration-waiting-stand-biv-3col.dat
EXPAR2.dat
Flow.dat
Flow394.dat
Geyser_waiting.dat
GSL.dat
GSL519.dat
Rain.dat
Rain394.dat
SSTdat
SSTgranite.dat

Yt-n500-sinus.dat
Computer Codes
Examples:
​​
Example_9-8.zip 
​Example_9-9.zip     
Example_9-10.zip   

Exercises:
Exercise_9-1.zip       
Exercise_9-2a-b.zip  
Exercise_9-2b.zip    
Exercise_9-4.zip       
Exercise_9-5.zip      
​
Miscellanea:
Algorithm-93.ox         
FCAR.zip        
FPE-additive.zip 
​Mean_median.m

​Figures 
Figures-Chapter-9-exercises.zip        
Figures-Chapter-9-exercises-jpg.zip 
​

(R code)
​(S-Plus)
(SAS code)


(M code)
(M code)
(R code)
(M code)
(R code)
​
(Ox code)
(S-Plus)
(G code)
(M code)
​

(EPS format)
​(JPEG format)​
​Links to  Websites with  Supplementary Material
  • Click on the following link for getting access to Ron Gallant's webpage with ​C code of SNP: A program for nonparametric time series analysis.  Reference: Gallant, A.R. and Tauchen, G. (1992), A nonparametric Approach to Nonlinear Time Series Analysis: Estimation and Simulation. In D.R. Brillinger et al. (Eds.) New Directions in Time Series Analysis, Part II. Spinger-Verlag, New York, pp. 71-92. Abstract: http://www.aronaldg.org/pubs/ima92.html.
  • Click on the following link for getting access to data sets, figures, and computer codes to accompany Fan and Yao (2003), Nonlinear Time Series: Nonparametric and Parametric Methods (Springer-Verlag, New York) .
  • Click on the following link for getting access to Gints Jekabsons' webpage with  the Adaptive Regression Splines (ARESLab) MATLAB/Octave toolbox.
  • ​Rafael A. Irizarry (2001, The American Statistician) presents a more general version of local (nonparametric) regression (e.g. Loess), called local harmonic regression or lohess. The S-Plus scripts used in the paper are available at: www.biostat.jhsph.edu/~ririzarr/software.html.
  • Click on the following link for downloading the kernel smoothing MATLAB toolbox, to accompany  Horová,  Koláček and  Zelinka, Kernel Smoothing in MATLAB: Theory and Practice of Kernel Smoothing. World Scientific Publishing Co. Pte. Ltd., 2012. 
  • Click on the following link for downloading MATLAB and R codes, to accompany the paper by Chen and Huo (2009, J. Computational and Statistical Graphics).
Last modified: May 2023

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